Analyze Image Content with OpenAI (ChatGPT) API on New Sponsorship Detected from Paved API

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New Sponsorship Detected from the Paved API

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Analyze Image Content with the OpenAI (ChatGPT) API

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Getting Started#

This integration creates a workflow with a Paved trigger and OpenAI (ChatGPT) action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Sponsorship Detected trigger
1. Connect your Paved account
2. Configure Polling Schedule
3. Select a Newsletter Slug
Configure the Analyze Image Content action
1. Connect your OpenAI (ChatGPT) account
2. Configure Message
3. Optional- Configure Image URL
4. Optional- Select a File ID
5. Optional- Configure File Path
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

New Sponsorship Detected on Paved

Description:Emit new event when a sponsorship is detected on a newsletter similar to yours. [See the documentation](https://docs.paved.com/list-sponsorships)

Version:0.0.1

Key:paved-new-sponsorship-detected

View on GitHub

Trigger Code#

import common from "../common/polling.mjs";

export default {
  ...common,
  key: "paved-new-sponsorship-detected",
  name: "New Sponsorship Detected",
  description: "Emit new event when a sponsorship is detected on a newsletter similar to yours. [See the documentation](https://docs.paved.com/list-sponsorships)",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getResourcesFn() {
      return this.app.listSponsorships;
    },
    getResourcesFnArgs() {
      return {
        debug: true,
        slug: this.slug,
      };
    },
    generateMeta(resource) {
      return {
        id: resource.id,
        summary: `New Sponsorthip: ${resource.advertiser_name}`,
        ts: Date.parse(resource.run_date),
      };
    },
  },
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
Paved	`app`	`app`	This component uses the Paved app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling Schedule	`timer`	`$.interface.timer`	How often to poll the API
Newsletter Slug	`slug`	`string`	Select a value from the drop down menu.

Trigger Authentication#

Paved uses API keys for authentication. When you connect your Paved account, Pipedream securely stores the keys so you can easily authenticate to Paved APIs in both code and no-code steps.

About Paved#

All-in-one Platform For Newsletter Sponsorships

Action#

Analyze Image Content on OpenAI (ChatGPT)

Description:Send a message or question about an image and receive a response. [See the documentation](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun)

Version:0.1.1

Key:openai-analyze-image-content

View on GitHub

OpenAI (ChatGPT) Overview#

OpenAI provides a suite of powerful AI models through its API, enabling developers to integrate advanced natural language processing and generative capabilities into their applications. Here’s an overview of the services offered by OpenAI's API:

Use Python or Node.js code to make fully authenticated API requests with your OpenAI account:

Action Code#

import openai from "../../openai.app.mjs";
import common from "../common/common-assistants.mjs";
import FormData from "form-data";
import fs from "fs";

export default {
  ...common,
  key: "openai-analyze-image-content",
  name: "Analyze Image Content",
  description: "Send a message or question about an image and receive a response. [See the documentation](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun)",
  version: "0.1.1",
  type: "action",
  props: {
    openai,
    message: {
      type: "string",
      label: "Message",
      description: "The message or question to send",
    },
    imageUrl: {
      type: "string",
      label: "Image URL",
      description: "The URL of the image to analyze. Must be a supported image types: jpeg, jpg, png, gif, webp",
      optional: true,
    },
    imageFileId: {
      propDefinition: [
        openai,
        "fileId",
        () => ({
          purpose: "vision",
        }),
      ],
      optional: true,
    },
    filePath: {
      type: "string",
      label: "File Path",
      description: "The path to a file in the `/tmp` directory. [See the documentation on working with files](https://pipedream.com/docs/code/nodejs/working-with-files/#writing-a-file-to-tmp)",
      optional: true,
    },
  },
  async run({ $ }) {
    const { id: assistantId } = await this.openai.createAssistant({
      $,
      data: {
        model: "gpt-4o", // replaced from "gpt-4-vision-preview" - see https://platform.openai.com/docs/deprecations
      },
    });

    const data = {
      assistant_id: assistantId,
      thread: {
        messages: [
          {
            role: "user",
            content: [
              {
                type: "text",
                text: this.message,
              },
            ],
          },
        ],
      },
      model: this.model,
    };
    if (this.imageUrl) {
      data.thread.messages[0].content.push({
        type: "image_url",
        image_url: {
          url: this.imageUrl,
        },
      });
    }
    if (this.imageFileId) {
      data.thread.messages[0].content.push({
        type: "image_file",
        image_file: {
          file_id: this.imageFileId,
        },
      });
    }
    if (this.filePath) {
      const fileData = new FormData();
      const content = fs.createReadStream(this.filePath.includes("tmp/")
        ? this.filePath
        : `/tmp/${this.filePath}`);
      fileData.append("purpose", "vision");
      fileData.append("file", content);

      const { id } = await this.openai.uploadFile({
        $,
        data: fileData,
        headers: fileData.getHeaders(),
      });

      data.thread.messages[0].content.push({
        type: "image_file",
        image_file: {
          file_id: id,
        },
      });
    }

    let run;
    run = await this.openai.createThreadAndRun({
      $,
      data,
    });
    const runId = run.id;
    const threadId = run.thread_id;

    run = await this.pollRunUntilCompleted(run, threadId, runId, $);

    // get response;
    const { data: messages } = await this.openai.listMessages({
      $,
      threadId,
      params: {
        order: "desc",
      },
    });
    const response = messages[0].content[0].text.value;
    return {
      response,
      messages,
      run,
    };
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
Message	`message`	`string`	The message or question to send
Image URL	`imageUrl`	`string`	The URL of the image to analyze. Must be a supported image types: jpeg, jpg, png, gif, webp
File ID	`imageFileId`	`string`	Select a value from the drop down menu.
File Path	`filePath`	`string`	The path to a file in the `/tmp` directory. See the documentation on working with files

Analyze Image Content with OpenAI (ChatGPT) API on New Sponsorship Detected from Paved API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), Paved and 2,200+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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